Conventional block-based image processing and analysis, such as image understanding, segmentation and compression, usually involves detecting the edge direction and the edge strength of a block. In ITU-T H.264/MPEG-4 AVC compliant encoding, the edge direction of a Macro-Block (MB) may provide important information about the prediction direction for intra-frame coding of the block and also for the block partition for inter-frame Motion Estimation (ME) and Motion Compensation (MC).
Several conventional approaches have been used to detect the edge direction of a block. Such approaches usually compute the gradient, the gradient direction and the gradient magnitude (amplitude) at each pixel of the block. The gradient direction at a particular pixel indicates the local edge direction in the neighborhood of the pixel. The gradient magnitude indicates the strength of the edge direction. In a conventional edge direction histogram method, the edge direction of a block is chosen in terms of the histogram of the edge directions of pixels in the block. In a conventional directional field method, the gradient information at the pixels of a block are pooled with two nonlinear spatial collapsing functions, and the quotient of the outcome of the two collapsing functions determines the edge direction of the block. Such approaches both involve pixel-wise nonlinear operations which are very expensive for hardware implementation and some software implementations.
In another conventional approach, the edge strength of a block is usually signified by the sum of the edge magnitude at each pixel of the block. The edge magnitude at a pixel is usually the absolute sum or the square root of the squared sum of the two gradient components at a particular pixel. Since the sum includes magnitudes of edges along all directions, the edge strength is not accurately reflected. Therefore, when used for block homogeneity detection, the edge strength may yield an inaccurate decision. In this context a block with high homogeneity has consistent texture information within its boundaries.